DBMS > HEAVY.AI vs. Lovefield vs. searchxml vs. Sqrrl

System Properties Comparison HEAVY.AI vs. Lovefield vs. searchxml vs. Sqrrl

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Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.

Description

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

DBMS for structured and unstructured content wrapped with an application server

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Relational DBMS

Native XML DBMS
Search engine

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.41
Rank	#153	Overall
	#71	Relational DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

www.searchxml.net/category/products

sqrrl.com

Technical documentation

docs.heavy.ai

github.com/google/lovefield/blob/master/docs/spec_index.md

www.searchxml.net/support/handouts

Developer

HEAVY.AI, Inc.

Google

informationpartners gmbh

Amazon

originally Sqrrl Data, Inc.

Initial release

2016

2014

2015

2012

Current release

5.10, January 2022

2.1.12, February 2017

1.0

License

Commercial or Open Source

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++ and CUDA

JavaScript

C++

Java

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
ODBC
Thrift
Vega

RESTful HTTP API
WebDAV
XQuery
XSLT

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

C++

most other programming languages supported via APIs

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

on the application server

Triggers

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

yes

sychronisation to multiple collections

selectable replication factor

making use of Hadoop

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

multiple readers, single writer

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

Domain, group and role-based access control at the document level and for application services

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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More resources

Recent citations in the news

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15 August 2024, Center for Data Innovation

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11 September 2024, insideBIGDATA

Dr. Mike Flaxman, VP or Product Management at HEAVY.AI – Interview Series
19 September 2024, Unite.AI

HEAVY.AI Accelerates Big Data Analytics with Vultr’s High-Performance GPU Cloud Infrastructure
11 September 2024, insideBIGDATA

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19 April 2023, businesswire.com

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